BNEFUNIVERSITY

BNEF UNIVERSITY

JENNY CHASEHead of Research, SolarBloomberg New Energy Finance

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PV INDUSTRY: BOOMING IN CRISIS

Falls in price are not purely due to margin compression – they are also due to gains in efficiency and cost

The entire PV value chain has been remarkably adept at reducing prices as incentives come down, and installation volumes continue to grow strongly

We expect installation growth to continue and prices to stabilise in 2013, although consolidation will continue

/ / / / / /

EBIT MARGINS OF PV MANUFACTURERS, Q4 2012

Source: Bloomberg New Energy Finance

The largest 17 quoted pureplay PV manufacturers made a total net loss of at least $8.9bn in 2011 and 2012

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THE PV MODULE EXPERIENCE CURVE, 1976–2012 ($/W)

Source: Paul Maycock, Bloomberg New Energy Finance

0.1

1

10

100

1 10 100 1,000 10,000 100,000 1,000,000

experience curve

1976

2006

2012

1985

2003

2012

experience curvehistoric prices (Maycock)Chinese c-Si module prices (BNEF)Thin-film experience curveFirst Solar thin-film module cost

Cost per W (2012$)

Cumulative capacity (MW)

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AVERAGE EFFICIENCY OF PV CELLS, 2010-2012 (%)

Source: Bloomberg New Energy Finance

17.5 17.7 17.216.2 16.3 16.1

18.2 18.1 18.216.8 16.7 16.8

18.6 18.5 18.617.0 17.0 17.0

Mono cellAverage all

mono

China mono Internationalmono

Average allmulti

China multi Internationalmulti

2010 2011 2012

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GERMAN PV COST AND REMUNERATION

0

100

200

300

400

500

600

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Q22006

Q12007

Q32007

Q12008

Q32008

Q12009

Q32009

Q12010

Q32010

Q12011

Q32011

Q12012

Q32012

Q12013

Capex sub 10kW (EUR/W) Feed-in tariff <10kW (EUR/MWh)

Residential power price (EUR/MWh) Commercial power price(EUR/MWh)

Source: BSW-Solar, Eurostat, Bloomberg New Energy Finance

EUR/W EUR/MWh

/ / / / / /

GERMAN PV COST AND REMUNERATION

Source: BSW-Solar, Eurostat, Bloomberg New Energy Finance

EUR/W EUR/MWh

0

100

200

300

400

500

600

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Q22006

Q12007

Q32007

Q12008

Q32008

Q12009

Q32009

Q12010

Q32010

Q12011

Q32011

Q12012

Q32012

Q12013

Capex sub 10kW (EUR/W) Feed-in tariff <10kW (EUR/MWh)

Residential power price (EUR/MWh) Commercial power price(EUR/MWh)

/ / / / / /

PV BUILD 2007-2012, CENTRAL FORECAST (MW/YEAR)

Source: Grid operations, incentive programme operators, industry associations, Bloomberg New Energy Finance

2.8GW6.6GW 7.7GW

18.2GW

28.7GW 30.6GW

35.7GW

46.6GW

54.5GW

2007 2008 2009 2010 2011 2012 2013 2014 2015Western Europe Eastern Europe Japan USAChina India Rest of World

Historical Forecast

BNEFUNIVERSITY

BNEF UNIVERSITY

JUSTIN WUHead of Research, WindBloomberg New Energy Finance

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THE WIND INDUSTRY IN 2013

Margin pressure

Manufacturing overcapacity – 2 times demand

Pricing pressure –27% drop since

2008

Market uncertainty – 17% drop in

demand in 2013

/ / / / / /

TRANSFORMATION OF WIND TURBINE MANUFACTURERS?

Equipment manufacturer

Energy service company

GearboxesBlades

Design Siting

O&M

Monitoring

Design

Gearboxes

Blades

/ / / / / /

TRANSFORMATION OF WIND TURBINE MANUFACTURERS?

Equipment manufacturer

Energy service company

MW MWh

/ / / / / /

TRANSFORMATION OF WIND TURBINE MANUFACTURERS?

Equipment manufacturer

Energy service company

Low margins

High competition

Less product differentiation

One off revenue

Higher margins

More product differentiation

Longer term revenue stream

/ / / / / /

HOW TO BECOME AN ENERGY SERVICES COMPANY?

Product differentiation – turbines designed for specific markets

Increase service revenue – bundle O&M contracts with turbines sales

Flexible manufacturing – quality instead of quantity

/ / / / / /

TURBINE PRODUCT STRATEGY

Target specific markets

Low wind speedsHigh altitudeExtreme environmentsOffshore wind

Diversify tech &

component risk

Lower costs & improve

output

Drive train configurationGeneratorsPower converters

Hub heightsRotor diameterImproved operations

/ / / / / /

PRICING BY TURBINE TYPE, 2008-13 (EUR M/MW)

1.10 1.10

1.21 1.20

1.061.02

0.980.94

0.900.85 0.82 0.82

0.99 0.99 1.02 0.99

H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2

2008 2009 2010 2011 2012 2013

WTPI Old models New models

16% average price gap

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O&M AND TURBINE SALES ANNUAL REVENUE POTENTIAL 2008-15E (EUR BN)

3.4 3.8 4.0 4.3 4.8 5.4 6.2 7.0

18.7

28.526.4

29.230.3

25.1

29.8 29.2

2008 2009 2010 2011 2012 2013 2014 2015

O&M Turbine sales

24%

17%

O&M will be ¼ of turbine

sales revenue by

2015

/ / / / / /

FLEXIBLE MANUFACTURING

Cut costs Expand into new markets

Reduce presence in

heavily oversupplied

markets

Meet local needs in new

markets (servicing,

local content requirement)

/ / / / / /

THE WIND INDUSTRY’S NEW ROI

Resilience: ability to survive pricing pressure and overcapacity in supply chain by rethinking business model

Optionality: selling more than one product, selling an energy service

Intelligence: specific products targeted to specific customers in specific markets

BNEF UNIVERSITY

MARK TAYLORHead of Research, Geothermal & CCSBloomberg New Energy Finance

BNEFUNIVERSITY

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ONLINE GEOTHERMAL POWER ASSETS

Just 11.4GW online globally

196GW estimated potential

/ / / / / /

ESTIMATED GEOTHERMAL RESOURCE POTENTIAL (MW)

113GW (est.) in 39 developing countries

Seen as economic development tool

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ANNOUNCED GEOTHERMAL PROJECTS

10.3GW (224 projects) stuck in pre-drilling

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PROJECTS STUCK BECAUSE OF DRILLING RISK

Sticking point

$m

Source: Bloomberg New Energy Finance

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A GLOBAL EXPLORATION DRILLING FUND

LOANS

COMMERCIAL BANK

LOANS

LOANS

DEVELOPMENT FINANCE ORG

GEOTHERMAL EXPLORATION DRILLING FUND

PORTFOLIO

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PROJECT SUCCESS PROBABILITY

DRILLING SUCCESS FACTORS FUND COSTS ($M)

44%

73%

62%55%

75%69%

0.34%

11% 13%

27% 30%

18%

100-150C

150-190C

190-230C

230-300C

300C+ Steamfield

Field success rate Field prevalence

1%5%

34%

60%

549

Set-up Admin Debt service Write-offs Total costs

Source: Bloomberg New Energy Finance, Rinova International, IFC

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INTEREST RATES CHARGED TO SUCCESSFUL PROJECTS

SENSITIVITY TO DRILLING SUCCESS SENSITIVITY TO COST OF CAPITAL

Historical weighted average success

0%

10%

20%

30%

40%

50%

60%

70%

40% 50% 60% 70% 80% 90%Drilling success rate

Multilateral3.5%

Private7%

0%

10%

20%

30%

40%

50%

60%

70%

0% 5% 10% 15%

WACCSource: Bloomberg New Energy Finance, Rinova International

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KEY TAKEAWAYS

Fund is feasible – provide access to capital

Leverage investment 1:18

Catalyse capacity expansion

BNEF UNIVERSITY

ALBERT CHEUNGHead of Research, Energy Smart TechnologiesBloomberg New Energy Finance

BNEFUNIVERSITY

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RESILIENCE: IMPACT OF SANDY ON THE POWER GRID

806

630

450300

156 14

LIPA JCP&L ConEd PSE&G CL&P Pepco

Total customers that lost power: 8.6m

SANDY STORM DAMAGE ESTIMATES OF SELECTED UTILITIES ($M)

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RESILIENCE: CAN SMART TECHNOLOGY HELP?

PEPCO (DC) – SANDY 2012

• 425,000 smart meters installed and activated at time of storm

• ‘Last-gasp’ functionality for outages

• Meters ‘pinged’ to locate faults

• Power restored to 130,000 homes in two days

VERMONT ELECTRIC COOP:OUTAGE FREQUENCY, 2005-2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Jan

-05

Jun

-05

Nov-0

5

Ap

r-0

6

Se

p-0

6

Feb

-07

Ju

l-07

Dec-0

7

May-0

8

Oct-

08

Mar-

09

Au

g-0

9

Jan

-10

Jun

-10

System average interruption frequency index (SAIFI)

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RESILIENCE: UTILITY RECONSTRUCTION PLANS ($M)

PUBLIC SERVICE ELECTRIC & GAS (NJ)CONSOLIDATED EDISON (NY)

240

200

165

106

10510060Upgrading selected ovehead lines

Network reconfiguration

Floodproof 460/208/120 volt equip

Gas system flood protection

Electric/steam flood barriers

Moving selected line underground

Substation flood barriers

976

1,700

1,040

454 215 200 140

60 Move 20 miles of lines undground

Protection of gas metering stations

Improve redundancies

Improve distribution lines

Smart grid deployment

Modernize gas mains

Upgrade switching/substations

3,809

Network reconfiguration

Smart grid deployment

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OPTIONALITY: MICROGRIDS

15

9

9

4.8

2.4110.5

Princeton distributedenergy resources (MW)

Back pressure steam turbine

Demand response

Diesel generation

CHP

PV

Chilled water storage

Steam-driven cooling

Gas turbine / HRSG

Total: 43MW

PRINCETON UNIVERSITY MICROGRID CASE STUDY

• Resilience: • Can provide power, cooling and heat to entire

campus in island mode, when utility is down• Optionality:

• Can use DERs to participate in wholesale and ancillary service markets

• Can purchase power in wholesale markets –arbitrage and hedging

• ‘Safe haven in the storm’ during Sandy

• Key enablers:• Smart microgrid technology• Renewable energy policy• Restructured market

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INTELLIGENCE: SMART ENERGY DATA APPLICATIONS

Geospatial visualisation tools for situational intelligence

Space-Time Insight

BuildingIQ

DataRaker/Oracle

Using near real-time data feeds to: • Predict

renewable generation

• Track outages• Monitor asset

health• Coordinate

emergency response

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INTELLIGENCE: SMART ENERGY DATA APPLICATIONS

Predictive optimisation of building energy use using building data, weather forecasts and demand response programme information

Utility DR programs,

pricing data

BMS system-HVAC

-Lighting-Occupancy

Weather data

Building optimisation

engine

Improved DR capacity and

overall building efficiency

Space-Time Insight

BuildingIQ

DataRaker/Oracle

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INTELLIGENCE: SMART ENERGY DATA APPLICATIONS

Cloud-based, big data tools to mine smart meter data

Using smart meter data analytics to:• Pinpoint energy

theft• Identify faulty

metering conditions

• Build asset utilisation profiles

Space-Time Insight

BuildingIQ

DataRaker/Oracle

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BNEF UNIVERSITY

HARRY BOYLEHead of Research, BioenergyBloomberg New Energy Finance

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BNEFUNIVERSITY

/ / / / / /

BIOENERGY MARKET SIZES, 2013 AND 2020

2013: $125bn

111

26

4

23

56

First-gen biofuels

Biomass-to-power

Waste-to-energy

BiochemsNext-gen biofuels

62

0.0011

20

41

First-gen biofuels

Biomass-to-power

Waste-to-energy

Biochems Next-gen biofuels

2020: $220bn

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FIRST-GENERATION BIOFUELS CAPACITY, 2004 – 2013 (M G ALLONS)

Source: Bloomberg New Energy Finance

10 1215

22

3135

39 41 42 42

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Hydrotreatment Transesterification 1-Gen fermentation

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OLD SCHOOL VERSUS NEW SCHOOL BIO -INNOVATION

SURPLUS BIOMASS INCINERATION POWER

SOFT COMMODITIES

FERMENTATION

ESTERIFICATION

ETHANOLBIODIESEL

Limited innovation; uses well known processes

UPSTREAM MIDSTREAM DOWNSTREAM

40 FEEDSTOCKS x 50 TECHNOLOGIES x 20 PRODUCTS = 40,000 THEORETICAL PATHWAYS

ALL BIOMASSMULTIPLEPATHWAYS

TAILORED PRODUCTS

/ / / / / /

SELECTED BIOENERGY PATHWAYS

GRAINS;SUGARCANE

AGRICULTURAL RESIDUES; WASTE; WOOD; ENERGY

CROPS

OILS, FATS, WASTE HYDROTREATMENT

GASIFICATION

TRANSESTERFICATION

FERMENTATION

ENZYMATIC / ACID HYDROLYSIS & FERMENT.

INCINERATION; GASIFICATION; CO-FIRING

ANAEROBIC DIGESTION

BIODIESEL, RENEWABLE DIESEL

ETHANOL, BUTANOL

ELECTRICITY, BIOMETHANE

SOLVENTS, PAINTS, LUBRICANTS, COSMETICS,

PLASTICS, RUBBERS

DIE

SE

LG

AS

.P

OW

ER

CH

EM

ICA

LS

FEEDSTOCKS TECHNOLOGIES PRODUCTS

/ / / / / /

TECHNOLOGY GLOBAL SHAKE OUT

ENERGY CROPS D1 OILS, MENDEL

CORN / WHEAT

MUNICIPAL WASTEFULCRUM, ENERKEM

JATROPHA

AG. RESIDUESPOET, DUPONT

SUGARCANE

WASTE GASESLANZATECH, JOULE

GASIFICATIONRENTECH, CHOREN, CHEMREC

PYROLYSISDYNAMOTIVE

TRANSESTERIFICATION

TORREFACTION

ENZYMATIC HYDROLYSISDSM, M&G, NOVOZYMES, RAIZEN

ADVANCED FERMENTATION MYRIANT, COBALT, AMYRIS

HYDROTREATMENT NESTE OIL, DIAMOND GREEN

ISOBUTANOL BUTAMAX, GEVO

N-BUTANOL GREEN BIOLOGICS

FARNESENE AMYRIS

HVO NESTE OIL, DYNAMIC

BIOCHEMICALSSOLAZYME, GENOMATICA

BIODIESEL

TORREFIED PELLETS

ALGAL BIOFUELSSYNTHETIC GENOMICS

BIOGASOLINELS9, PRIMUS GREEN ENERGY

FEEDSTOCKS TECHNOLOGIES PRODUCTS

ST

RU

GG

LIN

GS

TIL

L G

OIN

G

/ / / / / /

CELLULOSIC ETHANOL COSTS ($ PER GALLON)

2012 2016

3.56

0.95

1.46

0.19 0.56

0.220.15 0.18 -0.17

Fe

ed

sto

ck

Cap

ex

Pre

tre

atm

en

t

Enzym

atic h

yd

roly

sis

Fe

rme

nta

tio

n

Lab

ou

r

Utilitie

s

By-p

rodu

cts

Tota

l

2.55

0.85

1.14

0.10 0.29

0.09 0.090.18 -0.19

Fe

ed

sto

ck

Ca

pex

Pre

tre

atm

en

t

Enzym

atic h

yd

roly

sis

Ferm

enta

tion

La

bo

ur

Utilitie

s

By-p

rod

ucts

To

tal

/ / / / / /

NEW TECHNOLOGY GLOBAL LANDSCAPE

SUGARCANE AG. RESIDUES

“SIMPLE” “MORE COMPLEX”

SUGARS

TAILORED FATS / OILSFARNESENELAURIC ACIDOLEIC ACIDBIODIESEL

FUELSETHANOLBUTANOL

RENEWABLE DIESELBIOGASOLINE

CHEMICALSC2: ETHYLENE, MEG, PET

C3: PROPYLENE, ACRYLIC ACIDC4: BUTADIENE, BUTENE, BUTANOL

PR

OD

UC

TM

AR

KE

TF

EE

DS

TO

CK

PHARMACEUTICALS, TRANSPORT, FOOD,

PLASTICS ROAD, AVIATION & MARINE

PLASTICS, PAINTS, SOLVENTS, LUBRICANTS, RUBBER, PLASTICS

/ / / / / /

CONCLUSIONS

Do investors understand the dynamics of niche and bulk agricultural commodity markets well enough? Fingers burnt during 1-gen roll out

Bioenergy industry already shown its ability to innovate: now going through a natural shake-out stage, where some technologies pass and some fail

Steel going in ground for a dozen semi-commercial scale cellulosic ethanol plants, with well-capitalised players heavily involved: industry inflection point almost there